What Is Technical Debt? A Complete Guide

You buy the latest iPhone on credit. Turn to fast car loan services to get yourself those wheels you’ve been eyeing for a while. Take out a mortgage to realise your dream of being a homeowner. Regardless of the motive, the common denominator is going into financial debt to achieve something today, and pay it off in future, with interest. The final cost will be higher than the loan value that you took out in the first place. However, debt is not limited to the financial world.

Technical Debt Definition

Technical debt – which is also referred to as code debt, design debt or tech debt – is the result of the development team taking shortcuts in the code to release a product today, which will need to be fixed later on. The quality of the code takes a backseat to issues like market forces, such as when there’s pressure to get a product out there to beat a deadline, front-run the competition, or even calm jittery consumers. Creating perfect code would take time, so the team opts for a compromised version, which they will come back later to resolve. It’s basically using a speedy temporary fix instead of waiting for a more comprehensive solution whose development would be slower.

How rampant is it? 25% of the development time in large software organisations is actually spent dealing with tech debt, according to a multiple case study of 15 organizations. “Large” here means organizations with over 250 employees. It is estimated that global technical debt will cost companies $4 trillion by 2024.

Is there interest on technical debt?

When you take out a mortgage or service a car loan, the longer that it takes to clear it the higher the interest will be. A similar case applies to technical debt. In the rush to release the software, it comes with problems like bugs in the code, incompatibility with some applications that would need it, absent documentation, and other issues that pop up over time. This will affect the usability of the product, slow down operations – and even grind systems to a halt, costing your business. Here’s the catch: just like the financial loan, the longer that one takes before resolving the issues with rushed software, the greater the problems will pile up, and more it will take to rectify and implement changes. This additional rework that will be required in future is the interest on the technical debt.

Reasons For Getting Into Technical Debt

In the financial world, there are good and bad reasons for getting into debt. Taking a loan to boost your business cashflow or buy that piece of land where you will build your home – these are understandable. Buying an expensive umbrella on credit because ‘it will go with your outfit‘ won’t win you an award for prudent financial management. This also applies to technical debt.

There are situations where product delivery takes precedence over having completely clean code, such as for start-ups that need their operations to keep running for the brand to remain relevant, a fintech app that consumers rely on daily, or situations where user feedback is needed for modifications to be made to the software early. On the other hand, incurring technical debt because the design team chooses to focus on other products that are more interesting, thus neglecting the software and only releasing a “just-usable” version will be a bad reason.

Some of the common reasons for technical debt include:

  • Inadequate project definition at the start – Where failing to accurately define product requirements up-front leads to software development that will need to be reworked later
  • Business pressure – Here the business is under pressure to release a product, such as an app or upgrade quickly before the required changes to the code are completed.
  • Lacking a test suite – Without the environment to exhaustively check for bugs and apply fixes before the public release of a product, more resources will be required later to resolve them as they arise.
  • Poor collaboration – From inadequate communication amongst the different product development teams and across the business hierarchy, to junior developers not being mentored properly, these will contribute to technical debt with the products that are released.
  • Lack of documentation – Have you launched code without its supporting documentation? This is a debt that will need to be fulfilled.
  • Parallel development – This is seen when working on different sections of a product in isolation which will, later on, need to be merged into a single source. The greater the extent of modification on an individual branch – especially when it affects its compatibility with the rest of the code, the higher the technical debt.
  • Skipping industrial standards – If you fail to adhere to industry-standard features and technologies when developing the product, there will be technical debt because you will eventually need to rework the product to align with them for it to continue being relevant.
  • Last-minute product changes – Incorporating changes that hadn’t been planned for just before its release will affect the future development of the product due to the checks, documentation and modifications that will be required later on

Types of Technical Debt

There are various types of technical debt, and this will largely depend on how you look at it.

  • Intentional technical debt – which is the debt that is consciously taken on as a strategy in the business operations.
  • Unintentional technical debt – where the debt is non-strategic, usually the consequences of a poor job being done.

This is further expounded in the Technical Debt Quadrant” put forth by Martin Fowler, which attempts to categorise it based on the context and intent:

Technical Debt Quadrant

Source: MartinFowler.com

Final thoughts

Technical debt is common, and not inherently bad. Just like financial debt, it will depend on the purpose that it has been taken up, and plans to clear it. Start-ups battling with pressure to launch their products and get ahead, software companies that have cut-throat competition to deliver fast – development teams usually find themselves having to take on technical debt instead of waiting to launch the products later. In fact, nearly all of the software products in use today have some sort of technical debt.

But no one likes being in debt. Actually, technical staff often find themselves clashing with business executives as they try to emphasise the implications involved when pushing for product launch before the code is completely ready. From a business perspective, it’s all about weighing the trade-offs, when factoring in aspects such as the aspects market situation, competition and consumer needs. So, is technical debt good or bad? It will depend on the context. Look at it this way: just like financial debt, it is not a problem as long as it is manageable. When you exceed your limits and allow the debt to spiral out of control, it can grind your operations to a halt, with the ripple effects cascading through your business.

 

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ESOS Guide for UK Manufacturers Available

The Engineering Employers’ Federation (EEF) is the UK’s largest sectoral structure. Its goal is to promote the interests of manufacturing, engineering and technology-based businesses in order to enhance their competitiveness.

EEF has positioned itself in London and Brussels in order to be in a position to lobby at EU and Westminster level. Part of its role is helping its members adapt to change and capitalise on it. When it discovered that a third of UK manufacturers must comply with ESOS (and 49% had not even heard of it) EEF decided it was time to publish a handbook for its members.

According to EEF’s head of climate and environment policy Gareth Stace, For the many manufacturers that have already taken significant steps to improve energy efficiency, ESOS can be viewed as a ?stock taking exercise?, ensuring that momentum is maintained and new measures are highlighted and taken when possible?.

He goes on to add that others that have not begun the process should view it as an ‘impetus’ to go head down and find the most cost-effective ways to slash energy costs. Ecovaro adds that they would also have the opportunity to reduce carbon emissions almost as a by-product.

Firms with more than 250 employees, over 250 million revenue or both must comply with ESOS across all UK sectors. In simplest terms, they must have conducted an energy audit by 5th December 2015, and logged their energy saving plan with the Environmental Agency that is Britain?s sustainability watchdog.

The Department of Energy & Climate Change (DEEC) that oversees it believes that large UK businesses are wasting ?2.8 billion a year on electricity they do not need. Clearly it makes sense to focus on larger targets; however EcoVaro believes those halfway to the threshold should voluntarily comply if cutting their energy bills by 25% sounds appealing.

We are able to assist with interpreting their energy audits. These are often a matter of installing sub-meters at distribution points, and reading these for a few representative months to establish a trend. Meters are inexpensive compared to electricity costs, and maintenance teams can install them during maintenance shutdowns.

Ecovaro helps these firms process the data into manageable summaries using cloud-based technology. This is on a pay-when-used basis, and hence considerably cheaper than acquiring the software, or appointing a consultant.

Are Target Operating Models strategic compasses?

The short answer is they usually are, because every organisation needs a road-map of where they are going. Target operating models can be complex documents with illustrative details including project management structures, special tools, implementation procedures and management metrics. They can also be simple statements, as for example Winston Churchill?s promise that ?we shall fight them on the beaches, on the landing grounds and in the fields? which gave Britain the strategic direction it needed.

Many initiatives unfortunately fail because managers are ?too busy? to bottom on what their target operating model should say, or simply don’t believe in paperwork. As a result, promising initiatives may blunder off course or die a slow death without them really noticing. We cannot manage what we cannot measure, which is where the management metrics fit in. One of my favourite quotes is ?if you don’t know where you are going any road will get you there? which is what the Cheshire Cat said to Alice in Wonderland when she got lost.

The author blundered through life without a plan because there was no one else with his particular brand of imagination. The current business climate is different because everybody is trying to ramp up, and investors want to know exactly what is going to happen to their money and by when. Hence a target operating model can be indispensable throughout a change or product cycle.

The benefits of having a measurable operations / technology plan can produce powerfully tangible results if the organisation follows through on it. Built-in metrics with milestones are powerful tool for management, and, when they map through to the company financial plan almost irreplaceable as cash-flow forecasters.

Other benefits may include:

  • Shorter times to market and greater agility when launching new ideas
  • Reduced investor risk through a predictable process that’s readily monitored
  • A stable operating environment where there is consensus on direction
  • Greater likelihood of delivering on time and leading to repeat orders
  • A more cost-effective process, with less risk of loss of quality and money

Although it dates back a few years the Wills UK and Ireland Retail model still provides an excellent benchmark of a target operating plan that worked. The strategic goals were exceptionally clear, and they brought in a proven project manager to help them drive the program forward.

We have delivered advanced business management services to many of our clients, and believe you will find our personalised approach time-efficient and effective too.

A Definitive List of the Business Benefits of Cloud Computing ? Part 4

Lowers cost of analytics

Big data and business intelligence (BI) have become the bywords in the current global economy. As consumers today browse, buy, communicate, use their gadgets, and interact on social networks, they leave in their trail a whole lot of data that can serve as a goldmine of information organisations can glean from. With such information at the disposal of or easily obtainable by businesses, you can expect that big data solutions will be at the forefront of these organisations’ efforts to create value for the customer and gain advantage over competitors.

Research firm Gartner’s latest survey of CIOs which included 2,300 respondents from 44 countries revealed that the three top priority investments for 2012 to 2015 as rated by the CIOs surveyed are Analytics and Business Intelligence, Mobile Technologies, and Cloud Computing. In addition, Gartner predicts that about $232 million in IT spending until 2016 will be driven by big data. This is a clear indication that the intelligent use of data is going to be a defining factor in most organisations.

Yet while big data offers a lot of growth opportunities for enterprises, there remains a big question on the capability of businesses to leverage on the available data. Do they have the means to deploy the required storage, computing resources, and analytical software needed to capture value from the rapidly increasing torrent of data?

Without the appropriate analytics and BI tools, raw data will remain as it is – a potential source of valuable information but always unutilised. Only when they can take the time, complexity and expense out of processing huge datasets obtained from customers, employees, consumers in general, and sensor-embedded products can businesses hope to fully harness the power of information.

So where does the cloud fit into all these?

Access to analytics and BI solutions have all too often been limited to large corporations, and within these organisations, a few business analysts and key executives. But that could quickly become a thing of the past because the cloud can now provide exactly what big data analytics requires – the ability to draw on large amounts of data and massive computing power – at a fraction of the cost and complexity these resources once entailed.

At their end, cloud service providers already deal with the storage, hardware, software, networking and security requirements needed for BI, with the resources available on an on-demand, pay-as-you-go approach. In doing so, they make analytics and access to relevant information simplified, and therefore more ubiquitous in the long run.

As the amount of data continues to grow exponentially on a daily basis, sophisticated analytics will be a priority IT technology across all industries, with organisations scrambling to find impactful insights from big data. Cloud-based services ensure that both small and large companies can benefit from the significantly reduced costs of BI solutions as well as the quick delivery of information, allowing for precise and insightful analytics as close to real time as possible.

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